Date of Award
2020
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Electrical Engineering
First Advisor
Tian . Xia
Second Advisor
Safwan . Wshah
Abstract
In this research, we investigate a data processing method to capture the respiratory rate of a person by utilizing a doppler radar to monitor their body movement during respiration. We utilize a machine learning algorithm with a radar sensor to capture the chest movement of a person while breathing and determine the respiratory rate according to that movement. We are using a Random Forest classifier to distinguish between different classes of pulses. After that, the algorithm constructs a sinusoidal signal representing the breathing rate of the sample. By applying this technique, we can detect the breathing rate accurately for different subjects by analyzing the evolution of the reflected pulse while breathing. Furthermore, we can detect the change in pulse width ratio between the pulses of the classes across multiple breaths
Language
en
Number of Pages
65 p.
Recommended Citation
Elhadad, Anwar, "Utilizing Machine Learning For Respiratory Rate Detection Via Radar Sensor" (2020). Graduate College Dissertations and Theses. 1178.
https://scholarworks.uvm.edu/graddis/1178